Efforts to automate the control of complex connection-based systems such as, for instance, engineering plants aboard naval vessels have emphasized the infrastructure and diagnostic aspects of plant management, i.e., monitoring subsystems via sensors and presentation of the sensor data to human operators. Interpretation of and response to the data remain largely manual tasks. This interpretation and response function, especially in damage control scenarios, is a significant factor in determining manpower levels. If the incident assessment and response loop can be closed with a reliable autonomous reasoning process, significant relief in overall manpower levels can be realized. The best automation efforts to date have been based on expert diagnostic knowledge in the form of coded rules or procedures that are interpreted by the system at runtime to detect, predict, or diagnose fault conditions. However, even the best automation efforts require significant amounts of human diagnosis and input.